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» On the Brittleness of Evolutionary Algorithms
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GECCO
2005
Springer
157views Optimization» more  GECCO 2005»
15 years 11 months ago
Simple addition of ranking method for constrained optimization in evolutionary algorithms
During the optimization of a constrained problem using evolutionary algorithms (EAs), an individual in the population can be described using three important properties, i.e., obje...
Pei Yee Ho, Kazuyuki Shimizu
PDP
2003
IEEE
15 years 11 months ago
A Parallel Evolutionary Algorithm for Circuit Partitioning
As general-purpose parallel computers are increasingly being used to speed up different VLSI applications, the development of parallel algorithms for circuit testing, logic minimi...
Raul Baños, Consolación Gil, Maria D...
CEC
2009
IEEE
15 years 10 months ago
Performance of infeasibility driven evolutionary algorithm (IDEA) on constrained dynamic single objective optimization problems
Abstract—A number of population based optimization algorithms have been proposed in recent years to solve unconstrained and constrained single and multi-objective optimization pr...
Hemant K. Singh, Amitay Isaacs, Trung Thanh Nguyen...
GECCO
2006
Springer
207views Optimization» more  GECCO 2006»
15 years 9 months ago
Both robust computation and mutation operation in dynamic evolutionary algorithm are based on orthogonal design
A robust dynamic evolutionary algorithm (labeled RODEA), where both the robust calculation and mutation operator are based on an orthogonal design, is proposed in this paper. Prev...
Sanyou Y. Zeng, Rui Wang, Hui Shi, Guang Chen, Hug...
SOCO
2010
Springer
15 years 25 days ago
Designing multilayer perceptrons using a Guided Saw-tooth Evolutionary Programming Algorithm
In this paper, a diversity generating mechanism is proposed for an Evolutionary Programming (EP) algorithm that determines the basic structure of Multilayer Perceptron classifiers ...
Pedro Antonio Gutiérrez, César Herv&...